Countrywide population movement monitoring using mobile devices generated (big) data during the COVID-19 crisis.

Mobile phones have been used to monitor mobility changes during the COVID-19 pandemic but surprisingly few studies addressed in detail the implementation of practical applications involving whole populations. We report a method of generating a "mobility-index" and a "stay-at-home/resting-index" based on aggregated anonymous Call Detail Records of almost all subscribers in Hungary, which tracks all phones, examining their strengths and weaknesses, comparing it with Community Mobility Reports from Google, limited to smartphone data. The impact of policy changes, such as school closures, could be identified with sufficient granularity to capture a rush to shops prior to imposition of restrictions. Anecdotal reports of large scale movement of Hungarians to holiday homes were confirmed. At the national level, our results correlated well with Google mobility data, but there were some differences at weekends and national holidays, which can be explained by methodological differences. Mobile phones offer a means to analyse population movement but there are several technical and privacy issues. Overcoming these, our method is a practical and inexpensive way forward, achieving high levels of accuracy and resolution, especially where uptake of smartphones is modest, although it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring.

The dual effect of social ties on COVID-19 spread in Japan.

We investigate why some communities experience worse COVID-19 outcomes than others. Past studies have linked the resilience of communities against crisis to social vulnerability and the capacity of local governments to provide public goods and services like health care. Disaster studies, which frequently examine the effect of social ties and mobility, may better help illuminate the current spread of COVID-19. We analyze Japan's 47 prefectures from February 12 to August 31 using 62,722 individual confirmed cases of COVID-19, paired with daily tallies of aggregate Facebook user movement among neighborhoods. Controlling for mobility levels, health care systems, government finance, gender balance, age, income, and education levels of communities, our analysis indicates that areas with strong linking social ties see no or far lower levels of COVID-19 case rates initially. However, case fatality rates rise in such communities once the disease enters as they lack horizontal (bonding) ties which can mitigate its health impacts. We anticipate this study to be a starting point for broader studies of how social ties and mobility influence COVID-19 outcomes worldwide along with shining a light on how different types of social relationships play different roles as a crisis or disaster progresses.